in this paper, we propose a new full-fuzzy video ratecontrol algorithm (rca) for variable bit rate (vbr) videoapplications. the proposed rca provides high qualitycompressed video with a low degree computational complexity.by controlling the quantization parameter (qp) on a picturebasis, it produces vbr video bit streams. the proposed rcahas been implemented on the jm h.264/avc video codec andth...

Identifying exceptional students for scholarships is an essential part of the admissions process in undergraduate and postgraduate institutions, and identifying weak students who are likely to fail is also important for allocating limited tutoring resources. In this article, we have tried to design an intelligent system which can separate and classify student according to learning factor and pe...

In machine learning the Fuzzy c-Means algorithm (FCM) plays an important role. This prototype based unsupervised clustering method has been extensively studied and applied to a great variety of problems from different research areas like medicine and biology. Commonly the Euclidean distance is used as dissimilarity measure, although any dissimilarity measure would be suited. Recently divergence...

In recent past, vector quantization has been observed as an efficient technique for image compression. In general, image compression reduces the number bits required to represent an image. The main significance of image compression is that the quality of the image is preserved. This in turn increases the storage space and thereby the volume of the data that can

In this paper we propose a new observations selection technique in Vector Quantization context. The main idea is to select observations that are not representatives of their classes. The cells generated by the Vector Quantization are divided in regions of rejection. A number of controlled experiments were performed demonstrating the proposed methodology potentiality. Key-Words: Observations Sel...

In Part I of this paper [1], an equivalence between the concepts of fuzzy clustering and soft competitive learning in clustering algorithms is proposed on the basis of the existing literature. Moreover, a set of functional attributes is selected for use as dictionary entries in the comparison of clustering algorithms. In this paper, five clustering algorithms taken from the literature are revie...

In this paper, a new competition strategy for learning vector quantization is proposed. The simple competitive strategy used for learning vector quantization moves the winning prototype which is the closest to the newly given data pattern. We propose a new learning strategy based on k-nearest neighbor prototypes as the winning prototypes. The selection of several prototypes as the winning proto...

Neuro-fuzzy approach have attracted considerable attention in the computational intelligence and segmentation algorithms have been increasingly in developed in improving the accuracy of medical diagnosis. Fuzzy set attempts to represent the human perception whereas neural network attempt to emulate the architecture and information representation scheme of human brain. In this paper a comparativ...

Storaging or transmission of speech signals at very low bit rate is a hot area in the field of speech processing. We used stochastic inter-frame interpolators and vector quantization (VQ) as a new method for developing a high quality 1200 BPS speech vocoder. The objective and subjecgtive test results show that performance of the new vocoder is compairable with 4800 BPS standard vocoders (as CELP).

This paper proposes novel lossy image compression technique using hybrid wavelet transform and vector quantization. First hybrid wavelet transform consisting of two different component transforms is generated and applied on color images. Discrete Kekre transform (DKT) and Discrete Cosine transform (DCT) play role of base and local transform respectively in hybrid wavelet transform. In transform...